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Related Experiment Videos

Correcting missing-data bias in historical demography.

M A Jonker1, A W van der Vaart

  • 1Department of Mathematics, Faculty of Sciences, Vrije Universiteit Amsterdam, the Netherlands. majonker@few.vu.nl

Population Studies
|March 17, 2007
PubMed
Summary
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This study evaluates methods for correcting incomplete population history data, crucial for accurate mortality estimates in historical demography. Statistical models offer reliable accuracy and insights into migration patterns.

Area of Science:

  • Historical demography
  • Population studies
  • Statistical modeling

Background:

  • Population history studies often rely on incomplete life history records.
  • Family reconstitution data frequently experiences right-censored death dates due to migration, with unobserved censoring times.

Purpose of the Study:

  • To review and compare various methods for correcting mortality estimates in population history research.
  • To assess the performance of different correction techniques using simulated and historical data.

Main Methods:

  • Review of existing literature on mortality estimation correction methods.
  • Application and comparison of methods to simulated datasets.
  • Analysis of seventeenth-century English parish data (Reigate) using the reviewed methods.

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Main Results:

  • An ad hoc method proposed by Ruggles demonstrated reasonable performance.
  • Statistical model-based methods, when realistic, achieved comparable accuracy to other approaches.
  • Statistical models also enabled the estimation of additional demographic variables, such as migration timing.

Conclusions:

  • Methods based on realistic statistical models provide accurate mortality estimates in population history.
  • These advanced models offer the advantage of estimating other key demographic parameters, enhancing historical population analysis.